Conventionally, remote stations control unmanned vehicles. These unmanned vehicles may be self-controlling, or autonomous. Conventional unmanned systems may extend the vision and the reach of a Warfighter. However, the Warfighter may spend so much time managing these assets that the Warfighter may lose effectiveness as a Warfighter.
Autonomy can relieve a Warfighter of this burden. By limiting the required role of a Warfighter from command and control to command only, an unmanned system may move from force extension to force expansion. Collaboration may further move an unmanned system from force expansion to force multiplication. This may allow a Warfighter to perform his duties more effectively, more successfully, and more decisively.
However, an autonomous system may face increasing challenges in control techniques. An autonomous system must be aware of the environment and adapt plans based on changes in understanding of the environment. Control, therefore, ideally is flexible, both in development and in execution.
An autonomous system is given objectives to be achieved. These objectives may be as simple as monitor state and report problems, or complex, for example, assault and capture a target area. Also, a system may be given constraints, such as flight corridors, acceptable risks, or authorized targets. A challenge may then be to integrate these objectives and constraints with environmental state and system state to plan and execute a mission plan in order to achieve the input objectives without violating the constraints.
Furthermore, an autonomous system may itself consist of autonomous systems. Thus, the autonomy may also coordinate multiple autonomous systems to act in concert. The team of unmanned vehicles may have access to assets external to the autonomous team that would aid in performance of the mission. These assets should also be used in concert with the autonomous team.
Conventional systems focus on individual autonomy, ignoring an important facet of collaborative autonomy. Conventional systems are also monolithic insofar as a single control system performs all functions required. Conventional systems thus fail to recognize different disciplines needed to perform the various functions. For example, the conventional system requires awareness of its environment. This requires inferences and estimations of probabilities in a data rich environment. This is different from planning, which takes the estimate of the environment and attempts to optimize courses of actions that effect change to the environment.